Triple

T2614345
Position Surface form Disambiguated ID Type / Status
Subject Super Bowl V E58850 entity
Predicate halftimeShow P10817 FINISHED
Object Up with People E49869 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Up with People | Statement: [Super Bowl V, halftimeShow, Up with People]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Up with People
Context triple: [Super Bowl V, halftimeShow, Up with People]
  • A. Up With People chosen
    Up With People is an educational, music-based nonprofit organization best known for its large-scale, youth-led musical performances and international goodwill tours.
  • B. The Satisfied People
    "The Satisfied People" is a film featuring Russian actress Svetlana Khodchenkova in a notable role.
  • C. Among People
    Among People is an alternative title for the film "In the World."
  • D. Our Very Own
    "Our Very Own" is a 1950 American drama film starring Ann Blyth and Jane Wyatt that explores the emotional upheaval of a teenager who discovers she is adopted.
  • E. The Fun of It
    The Fun of It is a 1932 memoir by pioneering aviator Amelia Earhart, recounting her experiences in early aviation and encouraging women to pursue flying.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ab4ac444dc819099614e534dd6021f completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd87fb87c819093b02c67c76d51fd completed March 7, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69af83eb8b088190b1ea47c6d42033c5 completed March 10, 2026, 2:37 a.m.
Created at: March 6, 2026, 9:50 p.m.